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TIMER: A Web Server for Comprehensive Analysis of Tumor-Infiltrating Immune Cells.

ABSTRACT: Recent clinical successes of cancer immunotherapy necessitate the investigation of the interaction between malignant cells and the host immune system. However, elucidation of complex tumor-immune interactions presents major computational and experimental challenges. Here, we present Tumor Immune Estimation Resource (TIMER; cistrome.shinyapps.io/timer) to comprehensively investigate molecular characterization of tumor-immune interactions. Levels of six tumor-infiltrating immune subsets are precalculated for 10,897 tumors from 32 cancer types. TIMER provides 6 major analytic modules that allow users to interactively explore the associations between immune infiltrates and a wide spectrum of factors, including gene expression, clinical outcomes, somatic mutations, and somatic copy number alterations. TIMER provides a user-friendly web interface for dynamic analysis and visualization of these associations, which will be of broad utilities to cancer researchers. Cancer Res; 77(21); e108-10. ©2017 AACR.

SUBMITTER: Li T

PROVIDER: S-EPMC6042652 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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TIMER: A Web Server for Comprehensive Analysis of Tumor-Infiltrating Immune Cells.

Li Taiwen T Fan Jingyu J Wang Binbin B Traugh Nicole N Chen Qianming Q Liu Jun S JS Li Bo B Liu X Shirley XS

Cancer research 20171101 21

Recent clinical successes of cancer immunotherapy necessitate the investigation of the interaction between malignant cells and the host immune system. However, elucidation of complex tumor-immune interactions presents major computational and experimental challenges. Here, we present Tumor Immune Estimation Resource (TIMER; cistrome.shinyapps.io/timer) to comprehensively investigate molecular characterization of tumor-immune interactions. Levels of six tumor-infiltrating immune subsets are precal ...[more]

PMID: 29092952

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Project description:Background: Cancer patients often display dysfunctional antitumor T-cell responses. Because noteworthy benefits of immune checkpoint pathway blockade, such as programmed cell death protein 1 (PD-1) inhibitors, have been achieved in multiple advanced cancers, the next critical question is which mono-blockade or combinatorial blockade regimens may reinvigorate antitumor T-cell immunity in those cancer patients while limiting immune-related adverse effects. Method: This study recruited, in total, 172 primary cancer patients (131 were blood-tumor-matched patients) who were treatment-naïve prior to the surgeries or biopsies covering the eight most prevalent types of cancer. With access to fresh surgical samples, this study simultaneously investigated the ex vivo expression level of eight known immune checkpoint receptors [PD-1, cytotoxic T-lymphocyte antigen-4 [CTLA-4], T-cell immunoglobulin and mucin-domain containing-3 [Tim-3], 2B4, killer cell lectin like receptor G1 [KLRG-1], TIGIT, B- and T-lymphocyte attenuator [BTLA], and CD160] on tumor-infiltrating T cells (TILs) and paired circulating T cells in blood from a 131-patient cohort. Results: We found increased an expression of PD-1 and Tim-3 but a decreased expression of BTLA on TILs when compared with peripheral blood from multiple types of cancer. Moreover, our co-expression analysis of key immune checkpoint receptors delineates "shared" subsets as PD-1+Tim-3+TIGIT+2B4+KLRG-1-CTLA-4- and PD-1+TIGIT+2B4+Tim-3-KLRG-1-CTLA-4- from bulk CD8 TILs. Furthermore, we found that a higher frequency of advanced differentiation stage T cells (CD27-CCR7-CD45RA-) among the "shared" subset (PD-1+Tim-3+TIGIT+2B4+KLRG-1-CTLA-4-) in bulk CD8 TILs was associated with poorly differentiated cancer type in cervical cancer patients. Conclusions: To our knowledge, our study is the first comprehensive analysis of key immune checkpoint receptors on T cells in treatment-naïve, primary cancer patients from the eight most prevalent types of cancer. These findings might provide useful information for future design of mono-blockade/combinatorial blockades and/or genetically modified T-cell immunotherapy.

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Dataset Information

TIMER: A Web Server for Comprehensive Analysis of Tumor-Infiltrating Immune Cells.

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TIMER: A Web Server for Comprehensive Analysis of Tumor-Infiltrating Immune Cells.

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